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  <h1>Source code for federatedml.param.ftl_param</h1><div class="highlight"><pre>
<span></span><span class="ch">#!/usr/bin/env python</span>
<span class="c1"># -*- coding: utf-8 -*-</span>

<span class="c1">#</span>
<span class="c1">#  Copyright 2019 The FATE Authors. All Rights Reserved.</span>
<span class="c1">#</span>
<span class="c1">#  Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);</span>
<span class="c1">#  you may not use this file except in compliance with the License.</span>
<span class="c1">#  You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1">#      http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1">#  Unless required by applicable law or agreed to in writing, software</span>
<span class="c1">#  distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1">#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1">#  See the License for the specific language governing permissions and</span>
<span class="c1">#  limitations under the License.</span>
<span class="c1">#</span>
<span class="kn">from</span> <span class="nn">federatedml.param.base_param</span> <span class="k">import</span> <span class="n">BaseParam</span>


<div class="viewcode-block" id="FTLModelParam"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.FTLModelParam">[docs]</a><span class="k">class</span> <span class="nc">FTLModelParam</span><span class="p">(</span><span class="n">BaseParam</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Defines parameters for FTL model</span>

<span class="sd">    Parameters</span>
<span class="sd">    ----------</span>
<span class="sd">    max_iteration: integer, default: 10</span>
<span class="sd">        The number of passes over the training data (aka epochs), must be positive integer</span>

<span class="sd">    eps: numeric, default: 1e-3</span>
<span class="sd">        The converge threshold, must be positive number</span>

<span class="sd">    alpha: numeric, default: 100</span>
<span class="sd">        The weight for objective function loss, must be positive number</span>

<span class="sd">    is_encrypt: bool, default; True</span>
<span class="sd">        The indicator indicating whether we use encrypted version of ftl or plain version, must be bool</span>

<span class="sd">    enc_ftl: str default &quot;dct_enc_ftl&quot;</span>
<span class="sd">        The name for encrypted federated transfer learning algorithm</span>

<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">max_iteration</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">64</span><span class="p">,</span> <span class="n">eps</span><span class="o">=</span><span class="mf">1e-5</span><span class="p">,</span>
                 <span class="n">alpha</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">lr_decay</span><span class="o">=</span><span class="mf">0.001</span><span class="p">,</span> <span class="n">l2_para</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">is_encrypt</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">enc_ftl</span><span class="o">=</span><span class="s2">&quot;dct_enc_ftl&quot;</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">max_iter</span> <span class="o">=</span> <span class="n">max_iteration</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">=</span> <span class="n">batch_size</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">eps</span> <span class="o">=</span> <span class="n">eps</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">alpha</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">lr_decay</span> <span class="o">=</span> <span class="n">lr_decay</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">l2_para</span> <span class="o">=</span> <span class="n">l2_para</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">is_encrypt</span> <span class="o">=</span> <span class="n">is_encrypt</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">enc_ftl</span> <span class="o">=</span> <span class="n">enc_ftl</span>

<div class="viewcode-block" id="FTLModelParam.check"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.FTLModelParam.check">[docs]</a>    <span class="k">def</span> <span class="nf">check</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">model_param_descr</span> <span class="o">=</span> <span class="s2">&quot;ftl model param&#39;s &quot;</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_iter</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;max_iter&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_number</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">eps</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;eps&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_number</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;alpha&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_boolean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">is_encrypt</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;is_encrypt&quot;</span><span class="p">)</span>
        <span class="k">return</span> <span class="kc">True</span></div></div>


<div class="viewcode-block" id="LocalModelParam"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.LocalModelParam">[docs]</a><span class="k">class</span> <span class="nc">LocalModelParam</span><span class="p">(</span><span class="n">BaseParam</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Defines parameters for FTL model</span>

<span class="sd">    Parameters</span>
<span class="sd">    ----------</span>
<span class="sd">    input_dim: integer, default: None</span>
<span class="sd">        The dimension of input samples, must be positive integer</span>

<span class="sd">    encode_dim: integer, default: 5</span>
<span class="sd">        The dimension of the encoded representation of input samples, must be positive integer</span>

<span class="sd">    learning_rate: float, default: 0.001</span>
<span class="sd">        The learning rate for training model, must between 0 and 1 exclusively</span>


<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">input_dim</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">encode_dim</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">learning_rate</span><span class="o">=</span><span class="mf">0.001</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">input_dim</span> <span class="o">=</span> <span class="n">input_dim</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">encode_dim</span> <span class="o">=</span> <span class="n">encode_dim</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="n">learning_rate</span>

<div class="viewcode-block" id="LocalModelParam.check"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.LocalModelParam.check">[docs]</a>    <span class="k">def</span> <span class="nf">check</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">model_param_descr</span> <span class="o">=</span> <span class="s2">&quot;local model param&#39;s &quot;</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">input_dim</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">input_dim</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;input_dim&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">encode_dim</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;encode_dim&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_open_unit_interval</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">learning_rate</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;learning_rate&quot;</span><span class="p">)</span>
        <span class="k">return</span> <span class="kc">True</span></div></div>


<div class="viewcode-block" id="FTLDataParam"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.FTLDataParam">[docs]</a><span class="k">class</span> <span class="nc">FTLDataParam</span><span class="p">(</span><span class="n">BaseParam</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Defines parameters for FTL data model</span>

<span class="sd">    Parameters</span>
<span class="sd">    ----------</span>
<span class="sd">    file_path: str, default: None</span>
<span class="sd">        The file path to FTL data configuration JSON file, must be string or None</span>

<span class="sd">    n_feature_guest: integer, default: 10</span>
<span class="sd">        The number of features at guest side, must be positive integer</span>

<span class="sd">    n_feature_host: integer, default: 23</span>
<span class="sd">        The number of features at host side, must be positive integer</span>

<span class="sd">    overlap_ratio: float, default: 0.1</span>
<span class="sd">        The ratio of overlapping samples between guest and host, must between 0 and 1 exclusively</span>

<span class="sd">    guest_split_ratio: float, default: 0.9</span>
<span class="sd">        The ratio of number of samples excluding overlapping samples at guest side, must between 0 and 1 exclusively</span>

<span class="sd">    num_samples: numeric, default: None</span>
<span class="sd">        The total number of samples used for train/validation/test, must be positive integer or None. If None, all samples</span>
<span class="sd">        would be used.</span>

<span class="sd">    balanced: bool, default; True</span>
<span class="sd">        The indicator indicating whether balance samples, must be bool</span>

<span class="sd">    is_read_table: bool, default; False</span>
<span class="sd">        The indicator indicating whether read data from dtable, must be bool</span>

<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">file_path</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">n_feature_guest</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">n_feature_host</span><span class="o">=</span><span class="mi">23</span><span class="p">,</span> <span class="n">overlap_ratio</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">guest_split_ratio</span><span class="o">=</span><span class="mf">0.9</span><span class="p">,</span>
                 <span class="n">num_samples</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">balanced</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">is_read_table</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">file_path</span> <span class="o">=</span> <span class="n">file_path</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">n_feature_guest</span> <span class="o">=</span> <span class="n">n_feature_guest</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">n_feature_host</span> <span class="o">=</span> <span class="n">n_feature_host</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">overlap_ratio</span> <span class="o">=</span> <span class="n">overlap_ratio</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">guest_split_ratio</span> <span class="o">=</span> <span class="n">guest_split_ratio</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">num_samples</span> <span class="o">=</span> <span class="n">num_samples</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">balanced</span> <span class="o">=</span> <span class="n">balanced</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">is_read_table</span> <span class="o">=</span> <span class="n">is_read_table</span>

<div class="viewcode-block" id="FTLDataParam.check"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.FTLDataParam.check">[docs]</a>    <span class="k">def</span> <span class="nf">check</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">model_param_descr</span> <span class="o">=</span> <span class="s2">&quot;ftl data model param&#39;s &quot;</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">file_path</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">check_string</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">file_path</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;file_path&quot;</span><span class="p">)</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_samples</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">num_samples</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;num_samples&quot;</span><span class="p">)</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">n_feature_guest</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;n_feature_guest&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">n_feature_host</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;n_feature_host&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_boolean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">balanced</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;balanced&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_boolean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">is_read_table</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;is_read_table&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_open_unit_interval</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">overlap_ratio</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;overlap_ratio&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_open_unit_interval</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">guest_split_ratio</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;guest_split_ratio&quot;</span><span class="p">)</span>
        <span class="k">return</span> <span class="kc">True</span></div></div>


<div class="viewcode-block" id="FTLValidDataParam"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.FTLValidDataParam">[docs]</a><span class="k">class</span> <span class="nc">FTLValidDataParam</span><span class="p">(</span><span class="n">BaseParam</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Defines parameters for FTL validation data model</span>

<span class="sd">    Parameters</span>
<span class="sd">    ----------</span>
<span class="sd">    file_path: str, default: None</span>
<span class="sd">        The file path to FTL data configuration JSON file, must be string or None</span>

<span class="sd">    num_samples: numeric, default: None</span>
<span class="sd">        The total number of samples used for validation, must be positive integer or None. If None, all samples</span>
<span class="sd">        would be used.</span>

<span class="sd">    is_read_table: bool, default; False</span>
<span class="sd">        The indicator indicating whether read data from dtable, must be bool</span>

<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">file_path</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">num_samples</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">is_read_table</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">file_path</span> <span class="o">=</span> <span class="n">file_path</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">num_samples</span> <span class="o">=</span> <span class="n">num_samples</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">is_read_table</span> <span class="o">=</span> <span class="n">is_read_table</span>

<div class="viewcode-block" id="FTLValidDataParam.check"><a class="viewcode-back" href="../../../federatedml.param.html#federatedml.param.ftl_param.FTLValidDataParam.check">[docs]</a>    <span class="k">def</span> <span class="nf">check</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="n">model_param_descr</span> <span class="o">=</span> <span class="s2">&quot;ftl validation data model param&#39;s &quot;</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">file_path</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">check_string</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">file_path</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;file_path&quot;</span><span class="p">)</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_samples</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">check_positive_integer</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">num_samples</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;num_samples&quot;</span><span class="p">)</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">check_boolean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">is_read_table</span><span class="p">,</span> <span class="n">model_param_descr</span> <span class="o">+</span> <span class="s2">&quot;is_read_table&quot;</span><span class="p">)</span>
        <span class="k">return</span> <span class="kc">True</span></div></div>

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